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Elife ; 72018 04 05.
Artigo em Inglês | MEDLINE | ID: mdl-29620521

RESUMO

The evaluation of protein localization changes on a systematic level is a powerful tool for understanding how cells respond to environmental, chemical, or genetic perturbations. To date, work in understanding these proteomic responses through high-throughput imaging has catalogued localization changes independently for each perturbation. To distinguish changes that are targeted responses to the specific perturbation or more generalized programs, we developed a scalable approach to visualize the localization behavior of proteins across multiple experiments as a quantitative pattern. By applying this approach to 24 experimental screens consisting of nearly 400,000 images, we differentiated specific responses from more generalized ones, discovered nuance in the localization behavior of stress-responsive proteins, and formed hypotheses by clustering proteins that have similar patterns. Previous approaches aim to capture all localization changes for a single screen as accurately as possible, whereas our work aims to integrate large amounts of imaging data to find unexpected new cell biology.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Microscopia de Fluorescência/métodos , Proteoma/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/metabolismo , Frações Subcelulares/metabolismo , Biologia Computacional/métodos , Ontologia Genética , Ensaios de Triagem em Larga Escala , Humanos , Transporte Proteico , Proteoma/análise , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/crescimento & desenvolvimento , Proteínas de Saccharomyces cerevisiae/genética
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